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CRII: CPS: A Knowledge Representation and Information Fusion Framework for Decision Making in Complex Cyber-Physical Systems

CRII: CPS: A Knowledge Representation and Information Fusion Framework for Decision Making in Complex Cyber-Physical Systems
CRII:CPS:复杂网络物理系统决策的知识表示和信息融合框架
批准号:
1464279
负责人:
Soumik Sarkar
金额:
$17.49万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-05-15 至 2018-04-30

项目摘要

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中文摘要
翻译
这个数据驱动的网络物理系统决策(CPS)项目的重点是将数据科学和系统科学的工具结合在一起,开发新的工具,用于在复杂的网络物理系统(如电网、交通网络、发电厂和智能建筑)中分析和做出准确的决策,使其更安全、更高效和高度安全。该项目开发算法,实现软件,并使用大型综合建筑系统作为挑战应用领域演示概念验证。与目前的方法相比,在这项研究中开发的工具的潜在优势将是更高的准确性,更高的自动化程度和更低的实施成本。大多数最先进的方法使用临时规则和基于物理的模型来解决此类问题。然而,由于当前和未来大型互联系统的复杂性,它们缺乏准确性和可扩展性。本项目开发的工具将通过智能地使用系统生成的大量数据来显著缓解这些问题。该研究的理论方面将利用非线性动力学、信息论、机器学习和统计力学等固有的多学科概念。该研究项目主要支持研究生的跨学科教育和职业发展,并为STEM学科的高中生和本科生提供教育和推广计划。该项目与爱荷华州立大学建筑能源研究中心(CBER)合作,在一个真实的平台上展示成功。该中心为研究人员提供了一个独特的机会,在Interlock House测试台上测试和验证工具,该测试台是一个用于能源效率研究和数据验证的高端现场实验室。这增强了将新技术转化为商业现实的潜力。
英文摘要
This Data-driven Decision-making in Cyber-physical systems (CPS) project focuses on bringing tools from data science and systems science together to develop new tools for analyzing and making accurate decisions in complex cyber-physical systems (e.g., power-grid, transportation network, power plants and smart buildings) to make them safer, more efficient and highly secure. This project develops algorithms, implements software and demonstrates proof-of-concept using large integrated building system as a challenge application area. Potential advantages of the tools developed in this research over current methods will be higher degree of accuracy, increased automation and lower cost of implementation. Majority of state-of-the-art methods use ad-hoc rules and physics-based models for such problems. However, they lack in accuracy and scalability due to the very complex nature of current and future large interconnected systems. The tools developed in this project will alleviate these issues significantly via intelligent use of large volume of data generated from the systems. The theoretical aspect of the research will make use of inherently multidisciplinary concepts from Nonlinear Dynamics, Information Theory, Machine Learning and Statistical Mechanics. The research project primarily supports interdisciplinary education and career development of graduate students as well as offers education and outreach programs to high school and undergraduate students in STEM disciplines.The project engages the Center for Building Energy Research (CBER) at Iowa State to demonstrate success on a real platform. The center provides a unique opportunity to the researchers to test and validate the tools on the Interlock House test bed which is a high end field laboratory for energy efficiency research and data validation. This enhances the potential of transitioning the new technology toward commercial reality.
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会议论文
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